PeerDoc is a collaborative real-time rich-text editor with undo/redo, cursor tracking, inline comments, permissions/sharing control over documents, a change history. Things you would expect from a modern collaborative editor on the web.
But the main difference is that it combines two types of collaboration:
In 2013, I wrote how crowdsourcing could help break out of the language bubble we all find ourselves in when we search online. How our search results only come from the language we write our search keywords in. But since then, machine translation between languages has greatly improved. So why are we still in our language bubbles?
There are some rays of hope. Google is reportedly able to return you results from other languages when there are no good hits in your primary language. I have to say, though, that I have never experienced this. Maybe because I usually search in English. I would guess that when you search in smaller languages, you sometimes get English results added.
But I want the opposite. I want to see ideas and thoughts and solutions that might be available in other languages, the languages I do not speak, when I search in English. I want diversity. I think all the pieces to build this are available. Why is this not already available? Am I overlooking any obstacle to this?
Gravity seems to be our first and most important teacher. Patient, consistent and always present. Children can learn cause and effect through it. What happens if I lift an object and let go? Over and over again. On repeat. Always the same thing.
When we think about life in space. Can we raise children there? Can children grow up in zero gravity? Can they develop their mental abilities without having this teacher around them? Or will they develop in other ways? A different kind of logic?
Database-abstraction APIs where you write a query using the host programming language should not exist. Or more precisely, should not have to exist. For example, in Django you can query the database using the following Python code:
Which Django translates (roughly) into the following SQL:
SELECT * FROM blog_entry WHERE is_draft = true;
But why we cannot write SQL query directly as an SQL query, while retaining all other features Django offers through its database-abstraction API (database agnostic code, inputs to queries and outputs from queries being Python objects, etc.)? I claim there is no reason anymore for that.
I am a big fan of the application architecture promoted by Meteor. I like declarative programming. You describe what you want and not how and the system does the rest. Reactive programming is very similar. You define how outputs should be computed from inputs, but when is this computed and how it is composed with other computations is left to the system. So you can define what is read from the database and send to the client. And how it is read on the client and transformed and send to the UI library. And then UI library can render this data. And every time something changes, the rest gets automatically recomputed, refreshed, re-rendered.
Meteor is tightly linked with MongoDB. They developed a complex piece of technology to provide reactive queries. Reactive queries are queries which after providing initial results they also continue providing any changes to those results as input data used in queries change. While I like MongoDB, I still prefer consistency tools provided by traditional SQL databases: transactions, foreign keys, joins and triggers. They are close to declarative programming as well. You define relations between data once and then the system makes sure data is consistent. I had to implement many of those features on top of MongoDB, like my package PeerDB.
This is why I made
reactive-postgres node.js package.
It provides exactly such reactive queries, but for
PostgreSQL open source database. Its API is simple, on purpose, and because it should be. You provide a query,
you get initial data, and then you get all changes. Try it out.
Proof of work consensus protocol used in modern cryptocurrencies like Bitcoin and Ethereum consumes a lot of energy and requires participants to use their CPUs for mining instead of other useful work. But exactly this cost is why it is works to prevent Sybil attacks. One cannot participate in the selection of the next block without paying this cost, which makes the issue of puppet participants trying to influence block selection irrelevant, because they also have to do the work, and pay the cost.
In recent Intel CPUs a new set of instructions is available, SGX, which allows one to run code inside a special environment where even operating system cannot change its execution. In the paper we published (arXiv, Cryptology ePrint Archive) we explore consensus protocol designs using the Intel SGX technology, with the goal of making blockchain participation energy efficient, with low CPU usage, and to democratize mining so that participants can participate again with their general purpose computers (with Intel CPUs) instead of only with specialized ASICs.